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MRI radiomics independent of clinical baseline characteristics and neoadjuvant treatment modalities predicts response to neoadjuvant therapy in rectal cancer.

Authors :
Song M
Li S
Wang H
Hu K
Wang F
Teng H
Wang Z
Liu J
Jia AY
Cai Y
Li Y
Zhu X
Geng J
Zhang Y
Wan X
Wang W
Source :
British journal of cancer [Br J Cancer] 2022 Jul; Vol. 127 (2), pp. 249-257. Date of Electronic Publication: 2022 Apr 02.
Publication Year :
2022

Abstract

Background: To analyse the performance of multicentre pre-treatment MRI-based radiomics (MBR) signatures combined with clinical baseline characteristics and neoadjuvant treatment modalities to predict complete response to neoadjuvant (chemo)radiotherapy in locally advanced rectal cancer (LARC).<br />Methods: Baseline MRI and clinical characteristics with neoadjuvant treatment modalities at four centres were collected. Decision tree, support vector machine and five-fold cross-validation were applied for two non-imaging and three radiomics-based models' development and validation.<br />Results: We finally included 674 patients. Pre-treatment CEA, T stage, and histologic grade were selected to generate two non-imaging models: C model (clinical baseline characteristics alone) and CT model (clinical baseline characteristics combining neoadjuvant treatment modalities). The prediction performance of both non-imaging models were poor. The MBR signatures comprising 30 selected radiomics features, the MBR signatures combining clinical baseline characteristics (CMBR), and the CMBR incorporating neoadjuvant treatment modalities (CTMBR) all showed good discrimination with mean AUCs of 0.7835, 0.7871 and 0.7916 in validation sets, respectively. The three radiomics-based models had insignificant discrimination in performance.<br />Conclusions: The performance of the radiomics-based models were superior to the non-imaging models. MBR signatures seemed to reflect LARC's true nature more accurately than clinical parameters and helped identify patients who can undergo organ preservation strategies.<br /> (© 2022. The Author(s).)

Details

Language :
English
ISSN :
1532-1827
Volume :
127
Issue :
2
Database :
MEDLINE
Journal :
British journal of cancer
Publication Type :
Academic Journal
Accession number :
35368044
Full Text :
https://doi.org/10.1038/s41416-022-01786-7